You are a data architect. The data engineering team needs to configure a synchronization of data between an on
You are a data architect. The data engineering team needs to configure a synchronization of data between an on-premises Microsoft SQL Server database to Azure SQL Database. Ad-hoc and reporting queries are being overutilized the on-premises production instance. The synchronization process must: • Perform an initial data synchronization to Azure SQL Database with minimal downtime […]
You develop data engineering solutions for a company. The company has on-premises Microsoft SQL Server databas
You develop data engineering solutions for a company. The company has on-premises Microsoft SQL Server databases at multiple locations. The company must integrate data with Microsoft Power BI and Microsoft Azure Logic Apps. The solution must avoid single points of failure during connection and transfer to the cloud. The solution must also minimize latency. You […]
You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data
You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data solution to collect, process, and maintain data. The analytical data store performs poorly. You must implement a solution that meets the following requirements: • Provide data warehousing • Reduce ongoing management activities • Deliver SQL query responses […]
You need to implement a feature engineering strategy for the crowd sentiment local models.
What should you do? A. Apply an analysis of variance (ANOVA). B. Apply a Pearson correlation coefficient. C. Apply a Spearman correlation coefficient. D. Apply a linear discriminant analysis. Explanation: The linear discriminant analysis method works only on continuous variables, not categorical or ordinal variables. Linear discriminant analysis is similar to analysis of variance (ANOVA) […]
You are creating a machine learning model. You have a dataset that contains null rows.
You are creating a machine learning model. You have a dataset that contains null rows. You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset. Which parameter should you use? A. Replace with mean B. Remove entire column C. […]
You use Azure Machine Learning Studio to build a machine learning experiment.
You use Azure Machine Learning Studio to build a machine learning experiment. You need to divide data into two distinct datasets. Which module should you use? A. Assign Data to Clusters B. Load Trained Model C. Partition and Sample D. Tune Model-Hyperparameters Explanation: Partition and Sample with the Stratified split option outputs multiple datasets, partitioned […]
You must evaluate your model on a limited data sample by using k-fold cross validation. You start by configuri
You are solving a classification task. You must evaluate your model on a limited data sample by using k-fold cross validation. You start by configuring a k parameter as the number of splits. You need to configure the k parameter for the cross-validation. Which value should you use? A. k=0.5 B. k=0 C. k=5 D. […]
You need to normalize values to produce an output column into bins to predict a target column.
You are a data scientist using Azure Machine Learning Studio. You need to normalize values to produce an output column into bins to predict a target column. Solution: Apply a Quantiles binning mode with a PQuantile normalization. Does the solution meet the goal? A. Yes B. No Explanation: Use the Entropy MDL binning mode which […]
You are a data scientist using Azure Machine Learning Studio.
You are a data scientist using Azure Machine Learning Studio. You need to normalize values to produce an output column into bins to predict a target column. Solution: Apply an Equal Width with Custom Start and Stop binning mode. Does the solution meet the goal? A. Yes B. No Explanation: Use the Entropy MDL binning […]
You must clean the missing values using an appropriate operation without affecting the dimensionality of the f
You are analyzing a numerical dataset which contains missing values in several columns. You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set. You need to analyze a full dataset to include all values. Solution: Calculate the column median value and use the median value as the […]